Current radar systems are able to operate in several distinct modes, depending on the application. In Moving Target Indication (MTI) mode, typical radar systems focus a narrow beam over small regions in the field of view for small integration times on the order of milliseconds. However MTI-mode radars suffer from tradeoffs between the small integration time (that leads to low SNR values and coarse resolutions) as compared to the number of regions that can be observed. Furthermore, MTI systems can only detect velocities in a single direction, which allow for evasive maneuvers to avoid detection.
In synthetic aperture radar (SAR) mode, an image is constructed by integrating radar pulses from spatially diverse points in the platform's trajectory. This ‘synthetic aperture’ leads to 2-dimensional imaging as well as much finer resolutions than in MTI-mode, due to the ability to use longer integration times. However, these benefits do not come without cost. SAR was designed to image stationary scenes, consequently, moving targets cause phase errors in the reconstruction of a SAR image that lead to smearing and displacement of a target's energy signal.
Previous attempts to use SAR for moving target detection involved approaches entailing a high computational burden (due to the need for a great deal of image processing). Other attempts to improve the performance of SAR radar used for moving-target detection while minimizing the computational burden have resulted in detection performance decreasing when nearby targets are present, making them unsuitable for use in urban or semi-urban environments.
The ‘Gotcha’ radar concept employs a wide antenna beam, along with a high revisit rate and fine radar resolution to allow improved detection, tracking, and identification of ground targets. In an urban radar environment, clutter competing with moving target returns can be very strong, making it difficult to detect a target of interest, distinguish it from false alarms, and perform geolocation and tracking. Moreover, the targets of interest are expected to be maneuvering, which causes defocusing and reduction in amplitude of the target synthetic aperture radar (SAR) image signature. Urban environments are also likely to contain numerous moving targets producing SAR responses in the vicinity of targets being tracked, making mis-associations more likely.
An improved way to conduct high-value target tracking using multi-channel radar of highly-maneuverable, low-RCS targets (e.g., civilian vehicles and dismounts) even in the presence of bright, heterogeneous clutter (e.g., urban or semi-urban), or in high-traffic scenarios is needed.